WASTE

On July 30, an open-source project ran Kimi K3, a 2.78-trillion-parameter model that requires 1.42 TB of storage, on a MacBook Pro with 64 GB of RAM at 0.3 tokens per second, demonstrating that memory…

WASTE, an embeddable inference engine written in C with no third-party runtime dependencies, runs the complete open-weights Kimi K3 model—2.78 trillion parameters in a 982 GiB container—on a 64 GB Mac…

A developer has demonstrated running the full 2.78-trillion-parameter Kimi K3 model on a consumer 64 GB MacBook Pro using a custom inference engine called WASTE, achieving 0.32–0.34 tokens per second …